1. Field of Invention
The invention relates generally to digital data receivers.
2. Description of Related Art
The ever-increasing demand for high-speed wireless data transmission has posed great challenges for wireless system designers to achieve high-throughput wireless communications in radio channels with limited bandwidth. Multiple transmit and receive antennas are most likely to be the dominant solution in future broadband wireless communication systems, as the capacity of such a multiple-input multiple-output (MIMO) channel increases linearly with the minimum between the numbers of transmit and receive antennas in a rich-scattering environment, without increasing the bandwidth or transmitted power [1, 2, 3]. See the Appendix for references. Because of the extremely high spectrum efficiency, MIMO techniques have been incorporated into several standards of various wireless applications, such as the IEEE 802.11 a wireless LAN, the IEEE 802.16 wireless MAN, and the WCDMA standards.
The Bell-labs layered space-time (BLAST) architecture is an example of uncoded MIMO systems now under implementation. In the literature [4, 5, 6], different BLAST detection schemes have been proposed based on nulling and interference cancellation (IC), such as the method of zero-forcing (ZF) nulling and IC with ordering, and the method based on minimum mean-squared error (MMSE) nulling and IC with ordering. The performance of these simple detection strategies is significantly inferior to that of the maximum likelihood (ML) detection, whose complexity grows exponential in terms of the number of transmit antennas. In [7, 8, 9], sphere decoding is proposed as a near-optimal BLAST detection method, whose complexity is cubic in terms of the number of transmit antennas. As hard decision algorithms, the above schemes suffer performance losses when concatenated with outer channel decoder in coded MIMO systems. In [8], a list sphere decoding algorithm is proposed to yield soft-decision output by storing a list of symbol sequence candidates. However, the complexity is significantly increased compared with the original sphere decoding algorithm.
The present invention provides a new family of demodulation algorithms based on sequential Monte Carlo methods. The new algorithms may advantageously be used for soft MIMO demodulation and achieve near-optimal performance with low complexities.
The sequential Monte Carlo (SMC) methodology [10, 11, 12, 13, 14, 15] originally emerged in the field of statistics and engineering and has provided a promising new paradigm for the design of low complexity signal processing algorithms with performance approaching the theoretical optimum for fast and reliable communication in highly severe and dynamic wireless environments. The SMC can be loosely defined as a class of methods for solving online estimation problems in dynamic systems, by recursively generating Monte Carlo samples of the state variables or some other latent variables. In [10, 11, 12, 15], SMC has been successfully applied to a number of problems in wireless communications including channel equalization, joint data detection and channel tracking in fading channels, and adaptive OFDM receiver in time dispersive channels.